AI prompts
Control how the AI writes — brand voice, rules, and which of your product data it sees.
Every AI generator in Product Pelican runs on a prompt you can edit. The AI Prompts page is where you set your brand voice, add rules the AI must follow, and choose which parts of your product data it gets to see.
📸 Screenshot needed — the AI Prompts page with the prompt list on the left and an editor open on the right.
This is the highest-value ten minutes in the app. Editing the description prompt once, before a bulk run, is the difference between output you ship and output you rewrite.
The prompts
Prompts are grouped by what they apply to.
Products
Title
An improved, search-friendly product title
Products → Titles
Description
The product description
Products → Descriptions
Metafields
Values for metafields you choose, generated alongside the description
Products → Descriptions
Image Alt Text
A description of a product image
Products → Missing Alt Text
Category
The best-matching Shopify taxonomy category — and, optionally, the matching Google product category
Products → No Category
Category Attributes
Category-specific attributes — Colour, Size, Material…
Products → Missing Category Attributes
SEO
The SEO title and meta description
Products → SEO
FAQ Generation
Question-and-answer pairs
Product FAQ
Collections
Description
A collection description
Collections → Description
Banner Alt Text
A description of a collection banner image
Collections → Missing Banner Alt Text
SEO
The SEO title and meta description for a collection
Collections → SEO
FAQ Generation
Question-and-answer pairs for a collection page
Product FAQ → Collections
How prompts work
A prompt is plain instructions, not a template. You do not need placeholders or variable syntax — Product Pelican attaches the product data automatically before sending your instructions to the AI.
Each prompt's editor lists exactly what gets attached. For example, the description prompt automatically receives the product title, type, tags, the current description, any context metafields you've ticked, and — when image analysis is on — the product photos.
So write your prompt as direction:
Write in a warm, plain-spoken voice. Lead with what the product is and who it's for. Mention materials and care in the second paragraph. British English. No exclamation marks, no "elevate", no "curated". Two short paragraphs, under 120 words.
Rather than trying to describe the data.
What you can and can't change
Prompts replace the instruction and persona part of the request. The structural parts — the candidate category list, the required output format — are always added by the app, so a customised prompt cannot break the pipeline. Rewriting the category prompt changes how the AI chooses; it cannot make it return something the app can't read.
Feeding your own data in
Several prompts have a context metafield picker — a checklist of your product metafield definitions. Anything you tick is passed to the AI as additional context.
Available on: Title, Description, Metafields, and FAQ Generation.
This is how you get genuinely specific output. If you keep fabric composition, care instructions, dimensions or warranty terms in metafields, tick them, and generated copy will reference real facts instead of generalising from the title.
📸 Screenshot needed — the context metafield picker with several product metafields ticked.
Generating metafields alongside descriptions
The Metafields prompt is different from the others: instead of writing one field, it fills a set of metafields you nominate, in the same pass as the description.
For each metafield you configure, you give it:
the metafield to write to
its own prompt describing what should go in it
Then, whenever you generate descriptions, those metafields are generated too. In the results, the description and each metafield get their own accept checkbox, so you can take the metafields and reject the description or vice versa. Any configured field the AI returns empty is listed explicitly rather than silently skipped.
Google Shopping fields
The same pane has a Google Merchant Center section: a ready-made set of the fields a Google feed needs — condition, gender, age group, custom product and five custom labels — that you tick rather than having to create metafields for.
They generate and apply exactly like the metafields above, with one difference: fields with a fixed set of values (condition, gender, age group) are shown as a dropdown, and an answer outside Google's vocabulary is dropped rather than written.
The Google product category is separate again — it is switched on from the Category prompt and is a lookup rather than a generation. Full detail: Google Shopping fields.
📸 Screenshot needed — the Google Merchant Center section with condition and age group ticked.
Gender and age group are for apparel. Leave them off for homeware, tools or food — Google does not expect them there, and the AI will try to answer anyway.
Reviewing what the AI was thinking
Generated descriptions and metafields carry a Show thinking link exposing the reasoning behind the result.
It is worth reading when:
A result surprises you and you want to know which input caused it.
A generation failed — the transcript is still returned, and usually explains why.
You are tuning a prompt and want to see whether an instruction is landing.
Tips
Change one thing at a time. Generate for the same 5 products after each edit so you can attribute the difference.
Be specific about length. "Two short paragraphs, under 120 words" works; "concise" does not.
Ban your least favourite words explicitly. A list of forbidden phrases is more effective than describing a tone.
Test on your weirdest products. The ones with sparse data are where prompts break down.
Turn on image analysis before tuning description prompts — it changes the output substantially, so tuning without it means tuning twice.
Related pages
Image analysis — let the AI see your product photos.
Product audit — where the generators are used.
Google Shopping fields — filling the fields your product feed needs.
Product FAQ — the FAQ generator.
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